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AgentCore CLI

Create, develop, and deploy AI agents to Amazon Bedrock AgentCore

Overview

Amazon Bedrock AgentCore enables you to deploy and operate AI agents securely at scale using any framework and model. AgentCore provides tools and capabilities to make agents more effective, purpose-built infrastructure to securely scale agents, and controls to operate trustworthy agents. This CLI helps you create, develop locally, and deploy agents to AgentCore with minimal configuration.

🚀 Jump Into AgentCore

  • Node.js 20.x or later
  • uv for Python agents (install)

Installation

Upgrading from the Bedrock AgentCore Starter Toolkit? The old Python CLI conflicts with this package. If it is still installed, npm install will fail with an error telling you which package manager has it. Uninstall it first using whichever tool you originally used:

pip uninstall bedrock-agentcore-starter-toolkit    # if installed via pip
pipx uninstall bedrock-agentcore-starter-toolkit   # if installed via pipx
uv tool uninstall bedrock-agentcore-starter-toolkit # if installed via uv

If you need to bypass the check (for example, in CI), set AGENTCORE_SKIP_CONFLICT_CHECK=1 before installing.

npm install -g @aws/agentcore

Quick Start

Use the terminal UI to walk through all commands interactively, or run each command individually:

# Launch terminal UI
agentcore

# Create a new project (wizard guides you through agent setup)
agentcore create
cd my-project

# Test locally
agentcore dev

# Deploy to AWS
agentcore deploy

# Test deployed agent
agentcore invoke

Supported Frameworks

Framework Notes
Strands Agents AWS-native, streaming support
LangChain/LangGraph Graph-based workflows
Google ADK Gemini models only
OpenAI Agents OpenAI models only

Supported Model Providers

Provider API Key Required Default Model
Amazon Bedrock No (uses AWS credentials) claude-sonnet-4-5-20250929-v1
Anthropic Yes claude-sonnet-4-5-20250929
Google Gemini Yes gemini-2.5-flash
OpenAI Yes gpt-4o

Commands

Project Lifecycle

Command Description
create Create a new AgentCore project
dev Start local development server
deploy Deploy infrastructure to AWS
invoke Invoke deployed agents

Resource Management

Command Description
add Add agents, memory, identity, evaluators, targets
remove Remove resources from project

Note: Run agentcore deploy after add or remove to update resources in AWS.

Evaluations

Command Description
add evaluator Add a custom LLM-as-a-Judge evaluator
add online-eval Add continuous evaluation for live traffic
run evals Run on-demand evaluation against agent traces
evals history View past eval run results
pause online-eval Pause a deployed online eval config
resume online-eval Resume a paused online eval config

Project Structure

my-project/
├── agentcore/
│   ├── .env.local          # API keys (gitignored)
│   ├── agentcore.json      # Resource specifications
│   ├── aws-targets.json    # Deployment targets
│   └── cdk/                # CDK infrastructure
├── app/                    # Application code

App Structure

├── app/                    # Application code
│   └── <AgentName>/        # Agent directory
│       ├── main.py         # Agent entry point
│       ├── pyproject.toml  # Python dependencies
│       └── model/          # Model configuration

Configuration

Projects use JSON schema files in the agentcore/ directory:

  • agentcore.json - Agent specifications, memory, identity, evaluators, online evals
  • deployed-state.json - Runtime state in agentcore/.cli/ (auto-managed)
  • aws-targets.json - Deployment targets (account, region)

Capabilities

  • Runtime - Managed execution environment for deployed agents
  • Memory - Semantic, summarization, and user preference strategies
  • Identity - Secure API key management via Secrets Manager
  • Evaluations - LLM-as-a-Judge for on-demand and continuous agent quality monitoring

Documentation

Feedback & Issues

Found a bug or have a feature request? Open an issue on GitHub.

Security

See SECURITY for reporting vulnerabilities and security information.

License

This project is licensed under the Apache-2.0 License.